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DBMS > Apache Impala vs. Databricks vs. HBase

System Properties Comparison Apache Impala vs. Databricks vs. HBase

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatabricks  Xexclude from comparisonHBase  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopThe Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.Wide-column store based on Apache Hadoop and on concepts of BigTable
Primary database modelRelational DBMSDocument store
Relational DBMS
Wide column store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score78.61
Rank#15  Overall
#2  Document stores
#10  Relational DBMS
Score30.50
Rank#26  Overall
#2  Wide column stores
Websiteimpala.apache.orgwww.databricks.comhbase.apache.org
Technical documentationimpala.apache.org/­impala-docs.htmldocs.databricks.comhbase.apache.org/­book.html
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaDatabricksApache Software Foundation infoApache top-level project, originally developed by Powerset
Initial release201320132008
Current release4.1.0, June 20222.3.4, January 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoApache version 2
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java
Server operating systemsLinuxhostedLinux
Unix
Windows infousing Cygwin
Data schemeyesFlexible Schema (defined schema, partial schema, schema free)schema-free, schema definition possible
Typing infopredefined data types such as float or dateyesoptions to bring your own types, AVRO
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.noyesno
Secondary indexesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementswith Databricks SQLno
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
Java API
RESTful HTTP API
Thrift
Supported programming languagesAll languages supporting JDBC/ODBCPython
R
Scala
C
C#
C++
Groovy
Java
PHP
Python
Scala
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functions and aggregatesyes infoCoprocessors in Java
Triggersnoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factoryesMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDSingle row ACID (across millions of columns)
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nonoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC
More information provided by the system vendor
Apache ImpalaDatabricksHBase
Specific characteristicsSupported database models : In addition to the Document store and Relational DBMS...
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Apache ImpalaDatabricksHBase
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